A computational assessment of the electronic, thermoelectric, and defect properties of bournonite (CuPbSbS₃) and related substitutions

Abstract

Bournonite (CuPbSbS) is an earth-abundant mineral with potential thermoelectric applications. This material has a complex crystal structure (space group Pmn2 #31) and has previously been measured to exhibit a very low thermal conductivity (κ < 1 W m K at T ≥ 300 K). In this study, we employ high-throughput density functional theory calculations to investigate how the properties of the bournonite crystal structure change with elemental substitutions. Specifically, we compute the stability and electronic properties of 320 structures generated via substitutions {Na-K-Cu-Ag}{Si-Ge-Sn-Pb}{N-P-As-Sb-Bi}{O-S-Se-Te} in the ABCD formula. We perform two types of transport calculations: the BoltzTraP model, which has been extensively tested, and a newer AMSET model that we have developed and which incorporates scattering effects. We discuss the differences in the model results, finding qualitative agreement except in the case of degenerate bands. Based on our calculations, we identify p-type CuPbSbSe, CuSnSbSe and CuPbAsSe as potentially promising materials for further investigation. We additionally calculate the defect properties, finding that n-type behavior in bournonite and the selected materials is highly unlikely, and p-type behavior might be enhanced by employing Sb-poor synthesis conditions to prevent the formation of Sb defects. Finally, we discuss the origins of various trends with chemical substitution, including the possible role of stereochemically active lone pair effects in stabilizing the bournonite structure and the effect of cation and anion selection on the calculated band gap.

Computer-aided design of metal chalcohalide semiconductors: from chemical composition to crystal structure

“… 1 – 7 This has made it possible to virtually screen through enormous amounts of data in the search for promising materials for energy applications such as photovoltaics, 8 – 10 solar fuels, 11 – 15 and thermoelectrics. 16 – 18 Furthermore, these databases are facilitating the move towards more predictive materials design using data-mining, machine learning, and other statistical techniques to reveal hitherto undiscovered trends and rules. 19 – 29 In order to search for Earth-abundant materials for energy applications, it is important to move beyond known materials and extend screening criteria to new compositions and structures.…”

Accelerating the discovery of materials for clean energy in the era of smart automation

“…However, the advent of robust first-principles methods and highperformance computing resources has opened up the way for in silico materials design. For example, novel inorganic thermoelectric materials have recently been designed using a combination of high-throughput first-principles calculations and data-mined substitution rules [116][117][118][119][120] . There are also ongoing efforts to identify alternative inorganics 116,120 or materials composed of more abundant organics.…”

Finding a junction partner for candidate solar cell absorbers enargite and bournonite from electronic band and lattice matching

“…For bournonite, there is variation in the literature between experimental measurements on natural samples measuring n-type conductivity 38 and theoretical prediction of the defect physics suggesting the material will be intrinsically p-type and difficult to dope n-type 39 . Junction partners for enargite are screened based on the CBO only, while for bournonite the CBO and VBO are considered in turn to provide options for an p-type or n-type absorber layer.…”